In Miller’s study, published on February 21 in the Proceedings of the National Academy of Sciences, the authors, using a microarray-based approach, have evaluated the genomewide expression of 854 miRNAs in prefrontal cortex from subjects afflicted with schizophrenia and bipolar disorder. At an FDR of 5 percent, only two miRNAs, hsa-miR-132 and -132*, were significantly underexpressed in the schizophrenic group, and were subsequently verified in a second postmortem brain cohort. Over 200 gene targets for miR-132 were predicted and, based on the Ingenuity Pathway analysis, some of the gene targets were in pathways associated with synaptic functions, neuronal CREB signaling, and DNA methylation. As pointed out by the authors, these pathways have been involved in the glutamatergic and dopaminergic hypotheses of schizophrenia, and the fact that miR-132 could exercise control over gene targets belonging to these pathways lends additional support for the potential involvement of miR-132 in schizophrenia. Using mouse models, the authors have also provided evidence for a neurodevelopmental effect of miR-132, where they showed that the expression of miR-132 began to rise throughout the second week postnatally, reaching peak expression between the second and fourth weeks. Using the same model paradigm, the authors also provided functional evidence for reduced miR-132 expression, which was dependent on NMDA signaling in both adult and newborn animals. Interestingly, interfering with the NMDA signaling in newborn pups resulted in a significant reduction of miR-132 expression that was maintained throughout adulthood.

In contrast to previous studies (Kim et al., 2010; Moreau et al., 2011), Miller’s study did not identify any significantly dysregulated miRNAs in the bipolar group. While several reasons for this discrepancy (e.g., different platforms, analytical approaches) might be invoked, on a more conceptual level this observation somewhat resembles the initial GWAS results, where in different studies the same polymorphisms would show different, positive or negative patterns of association. As the power to detect true effects increases with sample size, it would be useful if a “meta-analysis” on existing miRNA, or total mRNA expressions for that matter, could be performed.

Another important aspect of all postmortem studies, including Miller’s, is adjusting for the effects of potential covariates. Although the postmortem brain banks provide detailed demographic information, the effect of antipsychotic treatment being confounded with diagnosis is especially difficult to parse out. In Miller’s study, the lifetime antipsychotic treatment did not appear to have a systemic effect on miRNA expressions. Of the reported miRNAs with detectable expression, only 4.5 percent were significantly affected by the antipsychotics. However, in their analyses, the lifetime antipsychotic treatment showed a highly significant effect on miR-132 expression; in fact, the significance levels of miR-132 association with disease and antipsychotics were essentially identical. Estimation of neuroleptics’ effect on miRNA expression becomes even more complicated, considering that the Stanley Foundation brains used in Miller’s study have fluphenazine equivalents rather than a measurement of antipsychotics. Since this measurement does not provide individual antipsychotic drug treatments, their effects on miRNA expression cannot be parsed out. Taken together, the lifetime drug intake coupled with lack of precise antipsychotic medication could explain the difference between the results from the animal models, where no effect of neuroleptics on miR-132 is seen, versus the strong effect of antipsychotics on miR-132 expression in the human postmortem brains.